Lung nodules diagnosis based on evolutionary convolutional neural network

被引：0

作者：

Giovanni L. F. da Silva

Otílio P. da Silva Neto

Aristófanes C. Silva

Anselmo C. de Paiva

Marcelo Gattass

机构：

[1] Federal University of Maranhão (UFMA),Applied Computing Group (NCA)

[2] Pontifical Catholic University of Rio de Janeiro - PUC - Rio,undefined

来源：

Multimedia Tools and Applications | 2017年 / 76卷

关键词：

Medical image; Lung nodules diagnosis; Deep learning; Genetic algorithm; Particle swarm optimization;

D O I：

暂无

中图分类号：

学科分类号：

摘要：

Lung cancer presents the highest cause of death among patients around the world, in addition of being one of the smallest survival rates after diagnosis. In this paper, we exploit a deep learning technique jointly with the genetic algorithm to classify lung nodules in whether malignant or benign, without computing the shape and texture features. The methodology was tested on computed tomography (CT) images from the Lung Image Database Consortium and Image Database Resource Initiative (LIDC-IDRI), with the best sensitivity of 94.66%, specificity of 95.14%, accuracy of 94.78% and area under the ROC curve of 0.949.

引用

页码：19039 / 19055

页数：16

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